Kinetica in Motion
The Kinetica Blog

What's New

Go to:

Forecasting Sales Using Regression Analysis and UDFs

By Karthik Lalithraj | September 15, 2017

Congratulations. You’ve just been promoted to Vice President of Data and Analytics at one of the largest American auto manufacturers. Before you’ve even had a chance to sit down, have a cup of coffee, and enjoy your corner office on the 45th floor, your new boss needs to see a forecast of new car sales of the…

How to query billions of rows from any BI tool…in seconds

By Jonathan Greenberg | August 3, 2017

These days, practically any BI tool might claim to query billions of rows. However, I’ve yet to see any BI tool, out of the box, do this in sub-second time using SQL query…until now. As a matter of fact, in my first four months with Kinetica, we’ve been able to do this with Tableau, Power…

12 Features to Look for When Choosing a GPU-Accelerated Analytics Database

By Amit Vij | August 2, 2017

GPU acceleration is revolutionizing high-performance computing. Leveraging GPUs for processing-intensive workloads is on the rise, particularly among verticals such as finance, retail, logistics, health/pharma, and government. GPU-acceleration is opening new possibilities for machine learning, deep learning, data visualization, or simply performing faster queries, joins and row-by-row math. If you’re investigating whether a GPU database can…

How GlaxoSmithKline Uses Kinetica to Manage Their R&D Information Platform

By Richard West | July 19, 2017

Mark Ramsey, SVP, R&D Data, at GlaxoSmithKline, spoke at a recent IBM/Kinetica executive breakfast, where he discussed how GSK uses GPUs and Kinetica to help transform the way that data is used as a strategic asset within their R&D organization. GlaxoSmithKline (GSK) is a science-led global healthcare company that researches and develops a broad range…

Interactive Spatial Analysis with Massive Datasets

By James Dilworth | July 12, 2017

As more and more data becomes available from sensors, from customers, from transactions—much of it with time and location information—there are increasing demands to analyze these data sets and visualize the results on maps. But today’s geospatial toolsets are hardly up to the task. Spatial databases weren’t designed for a world where IoT systems might…

In the press

Join us at these upcoming events